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WHAATRR gilder is a PRANDTL-M flying weather and space radiation sensor laden vehicle for identifying weather hazards for aviation safety.
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In support of the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project, a fleet of unmanned ground vehicles (UGVs) was developed as a test and evaluation (T\&E) platform to reduce system integration gaps between simulation and live flight hardware. While simulation and hardware-in-the-loop bench testing provide adequate environments for preliminary validation, differences in system deployment architecture, software interfaces, and hardware infrastructure increase the risks to safety, property, and the project. Given ATTRACTOR’s goal of establishing a basis of certification of trust and trustworthiness in multi-agent autonomous systems, bridging these gaps was critical to successful project execution and feasibility assessment. In this paper we present the UGV fleet and its role in speeding up system integration, smoothing the transition from simulation to flight, and providing researchers an easy-to-use hardware test bed. An overview of the hardware and software on-board the vehicles is provided along with supporting infrastructure. The system integration process is documented including results in supporting both the overarching design reference mission (DRM) of ATTRACTOR and individual research efforts conducted since the creation of the fleet. Finally, we discuss the practical lessons learned regarding the testing, deployment, and operation of multi-agent autonomous systems.
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Area-I partnered with the NASA SBIR/STTR program to develop Uncrewed Aircraft Systems (UASs) that supported advanced aeronautics research. The company’s developments with NASA culminated in the Prototype-Technology Evaluator and Research Aircraft (PTERA), a versatile UAS enabling low-risk flight experiments that are safer than piloted tests and more dynamic than wind tunnel testing. From the initial seed funding from NASA, Area-I continued to hone its abilities in UAS development, finding success with the Department of Defense and leading to the company’s acquisition by Anduril Industries—a $4.6 billion defense technology company—in 2021.
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We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.
We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.
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A Flash Lidar utilizing a novel Super-Resolution (SR) technique has been developed for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard landing vehicles. Processing algorithms for precision navigation and safe landing location identification take advantage of the uniform fixed pixels property of generated high resolution Digital Elevation Maps (DEMs) to achieve high reliability operation in near real-time. This paper describes the current and next generation breadboard units, report the results of recent dynamic tests, and explain the operational concept as envisioned for future landing missions.
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Urban aerial mobility vehicles and networks have recently gained considerable interest in the aviation community. These small, short-range vehicles with all-electric or hybrid-electric propulsion systems, tailored to metropolitan aerial transportation needs, promise to radically change passenger mobility and cargo distribution in cities. Accessibility issues have not been a major consideration in UAM vehicle and network discussions to date. This paper seeks to help change that.
Natural fliers demonstrate a diverse array of flight capabilities, many of which are poorly understood. NASA has established a research project to explore and exploit flight technologies inspired by biological systems. One part of this project focuses on dynamic modeling and control of micro aerial vehicles that incorporate flexible wing structures inspired by natural fliers such as insects, hummingbirds and bats. With a vast number of potential civil and military applications, micro aerial vehicles represent an emerging sector of the aerospace market. This paper describes an ongoing research activity in which mechanization and control concepts for biologically inspired micro aerial vehicles are being explored. Research activities focusing on a flexible fixed- wing micro aerial vehicle design and a flapping-based micro aerial vehicle concept are presented.
The advent of low earth orbit (LEO) commercial communication satellites provides an opportunity to dramatically reduce Telemetry, Tracking and Control (TT&C) costs of launch vehicles, Unpiloted Aerial Vehicles (UAVs), Research Balloons and spacecraft by reducing or eliminating ground infrastructure. Personnel from the Goddard Space Flight Center's Wallops Flight Facility (GSFC\WFF) have successfully used commercial Geostationary Earth Orbit (GEO) and Big LEO communications satellites for Long Duration Balloon Flight TT&C. The Flight Modem is a GSFC\WFF Advanced Range Technology initiative (ARTI) designed to streamline TT&C capability in the user community of these scientific data gathering platforms at low cost. Making use of existing LEO satellites and adapting and ruggedized commercially available components; two-way, over the horizon communications may be established with these vehicles at great savings due to reduced infrastructure. Initially planned as a means for permitting GPS data for tracking and recovery of sounding rocket and balloon payloads, expectations are that the bandwidth can soon be expanded to allow more comprehensive data transfer. The system architecture which integrates antennas, GPS receiver, commercial satellite packet data modem and a single board computer with custom software is described and technical challenges are discussed along with the plan for their resolution. A three-phase testing and development plan is outlined and the current results are reported. Results and status of ongoing flight tests on aircraft and sounding rockets are reported. Future applications on these platforms and the potential for satellite support are discussed along with an analysis of cost effectiveness of this method vs. other tracking and data transmission schemes.